Principles of Data Mining and Knowledge Discovery: First European Symposium, PKDD '97, Trondheim, Norway, June 24-27, 1997 Proceedings, Volume 1

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Springer Science & Business Media, 1997 M06 13 - 396 pages
This book constitutes the refereed proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery, PKDD '97, held in Trondheim, Norway, in June 1997.
The volume presents a total of 38 revised full papers together with abstracts of one invited talk and four tutorials. Among the topics covered are data and knowledge representation, statistical and probabilistic methods, logic-based approaches, man-machine interaction aspects, AI contributions, high performance computing support, machine learning, automated scientific discovery, quality assessment, and applications.
 

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Contents

Knowledge Discovery A Control Theory Perspective
1
Modelling Customer Retention with Rough Data Models
4
Share Based Measures for Itemsets
14
Parallel Knowledge Discovery Using Domain Generalization Graphs
25
Rough Set Theory and Rule Induction Techniques for Discovery of Attribute Dependencies in Medical Information Systems
36
Logical Calculi for Knowledge Discovery in Databases
47
Extraction of Experts Decision Process from Clinical Databases Using Rough Set Model
58
Discovering of Health Risks and CaseBased Forecasting of Epidemics in a Health Surveillance System
68
Towards ProcessOriented Tool Support for Knowledge Discovery in Databases
243
A Connectionist Approach to Structural Similarity Determination as a Basis of Clustering Classification and Feature Detection
254
Searching for Relational Patterns in Data
265
Finding Spatial Clusters
277
Interactive Interpretation of Hierarchical Clustering
288
Towards a Fair Evaluation of the CostEffectiveness of KDD Techniques
299
Recognizing Reliability of Discovered Knowledge
307
Clustering Techniques in Biological Sequence Analysis
315

An Algorithm for Multirelational Discovery of Subgroups
78
Finding Similar Time Series
88
A Novel Approach to Similarity Representation
101
Pattern Based Browsing in Document Collections
112
Induction of Fuzzy Characteristic Rules
123
RegressionBased Classification Methods and Their Comparison with Decision Tree Algorithms
134
Attribute Discovery and Rough Sets
145
Generation of Rules from Incomplete Information Systems
156
Rough Set Analysis and Its Interaction with GoalOriented Measurement
167
Efficient Multisplitting on Numerical Data
178
An Intelligent Assistant for Exploratory Data Analysis
189
Exploratory Analysis of Biochemical Processes Using Hybrid Modeling Methods
200
Using Signature Files for Querying TimeSeries Data
211
A New and Versatile Method for Association Generation
221
Bivariate Decision Trees
232
TOAS Intelligence Mining Analysis of Natural Language Processing and Computational Linguistics
323
Algorithms for Constructing of Decision Trees
335
Mining in the Phrasal Frontier
343
Mining Time Series Using Rough Sets A Case Study
351
Rough Set Approach to Continuous Data
359
On Meta Levels of an Organized Society of KDD Agents
367
Using Neural Network to Extract Knowledge from Database
376
Induction of Strong Feature Subsets
384
Rough Sets for Data Mining and Knowledge Discovery
393
Techniques and Applications of KDD
394
Data Mining
395
Data Mining in the Telecommunications Industry
396
Author Index
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